About the role
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
The future of Lyft is a hybrid network, where autonomous vehicles and human drivers serve riders side by side on one platform. That future has already started. In September 2026, Lyft riders in Nashville were matched with Waymo autonomous vehicles on the Lyft app for the first time, a milestone years in the making. Through Flexdrive, Lyft manages the depots, charging and maintenance that keep autonomous fleets on the road. Our partnerships now span Waymo in Nashville, May Mobility in Atlanta and Baidu in Europe, with more on the way.
We are early, and the playbook for running a hybrid marketplace at scale hasn't been written yet. You will help write it.
The Global Growth organization is charting the future of Lyft's growth beyond North American rideshare's core products. This includes our premium Luxury modes and Livery drivers, building a unified Lyft presence internationally, and bringing Autonomous Vehicles (AVs) to riders domestically and abroad. As the Staff Data Scientist for AV, you will be the science leader for one of the most strategic bets at the company. You will set the vision for how we measure, optimize and grow autonomous rides on Lyft, and you will shape the strategy behind which partners we work with, which markets we enter and which products we build to win.
This is a high-visibility role with direct exposure to Lyft's executive team and to our AV partners. You will work closely with engineering, product, operations, policy and partnership leaders, act as the bridge to our central marketplace science teams, and represent Lyft science in working sessions with partner teams. You will also have the opportunity to grow and define the AV science function as it scales.
The ideal candidate is a thought leader who pairs deep technical rigor with strong business judgment. You are as comfortable designing an experiment or building a causal model as you are walking a senior leader through a recommendation. In this role, you will help us tackle problems such as:
- Hybrid matching: When a rider requests a ride, how should the marketplace decide between an AV and a human driver, and how does that choice affect wait times, AV utilization and driver earnings?
- Incrementality: What is the true incremental value of an AV ride to Lyft, beyond the ride itself, and how do we translate partner metrics into Lyft's topline?
- Rider trust and adoption: What makes a rider choose, trust or opt out of an autonomous ride, and how should the product experience earn that trust?
- Partnership performance: What shared metrics and service quality guardrails should define success with each AV partner, and how do we use them to improve the product together?